1 code implementation • ACL 2022 • Urchade Zaratiana, Nadi Tomeh, Pierre Holat, Thierry Charnois
There are two main paradigms for Named Entity Recognition (NER): sequence labelling and span classification.
no code implementations • 18 Apr 2024 • Urchade Zaratiana, Nadi Tomeh, Yann Dauxais, Pierre Holat, Thierry Charnois
Joint entity and relation extraction plays a pivotal role in various applications, notably in the construction of knowledge graphs.
1 code implementation • 18 Apr 2024 • Urchade Zaratiana, Nadi Tomeh, Niama El Khbir, Pierre Holat, Thierry Charnois
Information extraction (IE) is an important task in Natural Language Processing (NLP), involving the extraction of named entities and their relationships from unstructured text.
Graph structure learning Joint Entity and Relation Extraction +1
1 code implementation • 2 Jan 2024 • Urchade Zaratiana, Nadi Tomeh, Pierre Holat, Thierry Charnois
In this paper, we propose a novel method for joint entity and relation extraction from unstructured text by framing it as a conditional sequence generation problem.
1 code implementation • 29 Nov 2023 • Urchade Zaratiana, Nadi Tomeh, Niama El Khbir, Pierre Holat, Thierry Charnois
Semi-Markov CRF has been proposed as an alternative to the traditional Linear Chain CRF for text segmentation tasks such as Named Entity Recognition (NER).
1 code implementation • 14 Nov 2023 • Urchade Zaratiana, Nadi Tomeh, Pierre Holat, Thierry Charnois
Named Entity Recognition (NER) is essential in various Natural Language Processing (NLP) applications.
1 code implementation • 26 Oct 2022 • Urchade Zaratiana, Niama El Khbir, Dennis Núñez, Pierre Holat, Nadi Tomeh, Thierry Charnois
Extractive question answering (ExQA) is an essential task for Natural Language Processing.
Ranked #2 on Question Answering on NaturalQA (F1 metric)
1 code implementation • 28 Mar 2022 • Urchade Zaratiana, Pierre Holat, Nadi Tomeh, Thierry Charnois
The task of Named Entity Recognition (NER) is an important component of many natural language processing systems, such as relation extraction and knowledge graph construction.
no code implementations • 8 Oct 2021 • Urchade Zaratiana
We demonstrate the effectiveness of our approach by evaluating the learned representation on the task of string similarity matching.